Book Image

The Deep Learning Workshop

By : Mirza Rahim Baig, Thomas V. Joseph, Nipun Sadvilkar, Mohan Kumar Silaparasetty, Anthony So
Book Image

The Deep Learning Workshop

By: Mirza Rahim Baig, Thomas V. Joseph, Nipun Sadvilkar, Mohan Kumar Silaparasetty, Anthony So

Overview of this book

Are you fascinated by how deep learning powers intelligent applications such as self-driving cars, virtual assistants, facial recognition devices, and chatbots to process data and solve complex problems? Whether you are familiar with machine learning or are new to this domain, The Deep Learning Workshop will make it easy for you to understand deep learning with the help of interesting examples and exercises throughout. The book starts by highlighting the relationship between deep learning, machine learning, and artificial intelligence and helps you get comfortable with the TensorFlow 2.0 programming structure using hands-on exercises. You’ll understand neural networks, the structure of a perceptron, and how to use TensorFlow to create and train models. The book will then let you explore the fundamentals of computer vision by performing image recognition exercises with convolutional neural networks (CNNs) using Keras. As you advance, you’ll be able to make your model more powerful by implementing text embedding and sequencing the data using popular deep learning solutions. Finally, you’ll get to grips with bidirectional recurrent neural networks (RNNs) and build generative adversarial networks (GANs) for image synthesis. By the end of this deep learning book, you’ll have learned the skills essential for building deep learning models with TensorFlow and Keras.
Table of Contents (9 chapters)
Preface

Introduction

How does Siri know exactly what to do when you ask her to "play a mellow song from the 80s"? How does Google find the most relevant results for even your ill-formed search queries in a fraction of a second? How does your translation app translate text from German to English almost instantly? How does your email client protect you and automatically identify all those malicious spam/phishing emails? The answer to all these questions, and what powers many more amazing applications, is using Natural Language Processing (NLP).

So far, we've dealt with structured, numeric data – images that were also numeric matrices. In this chapter, we'll begin our discussion by talking about handling text data and unlock the skills needed to harness this goldmine of unstructured information. We will discuss a key idea in this chapter – representation, particularly using embeddings. We will discuss the considerations and implement the approaches for representation...